/**
*  Copyright (c) 2011, Alex Theodoridis
*  All rights reserved.

*  Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
*  Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
*  Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following
*  disclaimer in the documentation and/or other materials provided with the distribution.

*  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
*  INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
*  IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
*  OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
*  OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
*  OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
*  EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE
*/

#ifndef DATA_H_
#define DATA_H_
#include <NeuralNetwork/NNException.h>
#include <vector>

class NNVar
{
public:
    static const unsigned int CONST_DEFAULT_NN_VAR_SIZE;

protected:
    std::vector<float> _values;

private:
    float GetAverage() const;

public:
    NNVar();
    NNVar ( float value );
    float& operator [] ( unsigned int index );
    NNVar operator * ( const NNVar& var ) const;
    NNVar operator - ( const NNVar& var ) const;
    NNVar operator + ( const NNVar& var ) const;
    NNVar operator / ( const NNVar& var ) const;
    const NNVar& operator += ( const NNVar& var );
    bool operator > ( const NNVar& var ) const;
    bool operator < ( const NNVar& var ) const;
    NNVar Sqrt() const;
    NNVar Pow ( NNVar& value );
    NNVar Exp();
    ~NNVar();
};

NNVar exp ( NNVar& var );

NNVar sqrt ( const NNVar& var );

NNVar pow ( NNVar& var,  NNVar& power );

#endif /* DATA_H_ */
